Nature-Inspired Computation and Swarm Intelligence

  • 7h 34m
  • Xin-She Yang
  • Elsevier Science and Technology Books, Inc.
  • 2020

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence.

In this Book

  • Nature-Inspired Computation and Swarm Intelligence—A State-of-the-Art Overview
  • Bat Algorithm and Cuckoo Search Algorithm
  • Firefly Algorithm and Flower Pollination Algorithm
  • Bio-Inspired Algorithms—Principles, Implementation, and Applications to Wireless Communication
  • Mathematical Foundations for Algorithm Analysis
  • Probability Theory for Analyzing Nature-Inspired Algorithms
  • Mathematical Framework for Algorithm Analysis
  • Fine-Tuning Restricted Boltzmann Machines Using Quaternion-Based Flower Pollination Algorithm
  • Traveling Salesman Problem—A Perspective Review of Recent Research and New Results with Bio-Inspired Metaheuristics
  • Clustering with Nature-Inspired Metaheuristics
  • Bat-Inspired Algorithm for Feature Selection and White Blood Cell Classification
  • Modular Granular Neural Network Optimization Using the Firefly Algorithm Applied to Time Series Prediction
  • Artificial Intelligence Methods for Music Generation—A Review and Future Perspectives
  • Optimized Controller Design for Islanded Microgrid Employing Nondominated Sorting Firefly Algorithm
  • Swarm Robotics – a Case Study—Bat Robotics
  • Electrical Harmonics Estimation in Power Systems Using Bat Algorithm
  • CSBIIST—Cuckoo Search-Based Intelligent Image Segmentation Technique
  • Improving Genetic Algorithm Solution Performance for Optimal Order Allocation in an e-Market with the Pareto-Optimal Set
  • Multirobot Coordination Through Bio-Inspired Strategies
  • Optimization in Probabilistic Domains—An Engineering Approach
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